code: def test_transformers_autolog_adheres_to_global_behavior_using_setfit(
      setfit_trainer,
  ):
      mlflow.transformers.autolog(disable=False)
  
      setfit_trainer.train()
      assert len(mlflow.search_runs()) == 0
      preds = setfit_trainer.model(
          ["Jim, I'm a doctor, not an archaeologist!"]
      )
      assert len(preds) == 1
  
imports: import random
  import numpy
  import optuna
  import pytest
  import sklearn
  import sklearn.cluster
  import torch
  from datasets import load_dataset
  from sentence_transformers.losses import CosineSimilarityLoss
  from setfit import SetFitModel, sample_dataset
  from setfit import Trainer
  from setfit import TrainingArguments
  from transformers import DistilBertForSequenceClassification, DistilBertTokenizerFast, Trainer, TrainingArguments, pipeline
  import mlflow
label_desc: Use image node_id 8 for calling a global function with example usage: test_transformers_autolog_adheres_to_global_behavior_using_setfit(setfit_trainer) without return types